Developed optimization models and search algorithms, in particular genetic algorithm and PSO, to find the best possible configurations of parameters in algorithm to optimize mining transport in real time.

Participation in the process of creating an artificial intelligence model that helps the Kaufmann company. The model predicts vehicle failures, to know what spare parts must be available and thus achieve the company’s goal: to reduce truck workshop times to improve customer service.Creation of a dynamic algorithm that allows automatic decisions to be made by a truck when its assigned task is canceled due to unforeseen events in the mine. This allows for the best possible performance for the mine's fleet of trucks and shovelParticipation of the business cases of the company's main Smart System, Octopus Mining Suite, where by means of Python the different input parameters required by the simulator were obtained, within these, the distributions of probability of shovel failures, the times of attention between each pair type shovel - type truck. The mine simulator was then validated and calibrated.Development of different digital panels made in Power BI that allow finding problems in different mine operations, such as shovel operators loading trucks with less material than they should, trucks with a malfunctioning scale or antenna, sectors of the mine with poor connectivity, operators reporting late arrivals at destinations, operators driving slower than they should, among others.Edition of a code that proactively identifies when users use the application incorrectly, generating an alert that allows these errors to be corrected before they affect the operation.Changes were made within the operation simulator that allow generating an output in the form of a table with data from the mining operation within the simulator. From this, panels were developed in Power BI that allow comparing what happens in reality with respect to the simulations, which allows corroborating that the simulations are being done correctly.

Participation in the warehouse areas, both in the reception of products and their respective process, and in inventory management. SQL, Python (Pandas) and Excel Macros were also used to automate emails for workers to choose their uniform sizes according to their function in the company.